class_docstr: Summary model of a trial component.
  
  Attributes:
      metric_name (str): The name of the metric.
      source_arn (str):  The ARN of the source.
      time_stamp (datetime): Metric last updated value.
      max (float): The max value of the metric.
      min (float):  The min value of the metric.
      last (float):  The last value of the metric.
      count (float):  The number of samples used to generate the metric.
      avg (float):  The average value of the metric.
      std_dev (float):  The standard deviation of the metric.
code: def __init__(self, metric_name=None, source_arn=None, **kwargs):
      super(TrialComponentMetricSummary, self).__init__(
          metric_name=metric_name, source_arn=source_arn, **kwargs
      )
  
imports: from __future__ import absolute_import
  import enum
  import numbers
  from sagemaker.apiutils import _base_types
label_desc: Use image node_id 1 to create a new TrialComponentMetricSummary object from inherited base classes: _base_types with example: obj = TrialComponentMetricSummary(metric_name, source_arn)